While providing remarkable insights into disease pathogenesis, genetic studies of psoriasis (and other immune-mediated inflammatory disorders (IMIDs) present several challenges. Thus, ~90% of IMID genetic signals do not appear to affect protein structure, mandating a search for genetic effects on gene regulation requiring study of disease-relevant cell types in physiologic context. Moreover, pathogenic cell types are often hard to access experimentally, and may be rare in diseased tissue. To address these challenges, we have developed several unique resources. We have completed a comparative GWAS of psoriatic arthritis (PsA) and purely cutaneous psoriasis (PsC), and a GWAS of psoriasis in India is nearing completion. We have generated RNA-seq based transcriptomes of normal vs. psoriatic skin, revealing expression quantitative trait loci (eQTL), critical transcriptional networks, and novel lncRNAs. We have developed advanced data-mining tools for elucidating the nature of non-coding genetic variation. Finally, we have extensive capabilities to study psoriasis biology in lymphocytes, dendritic cells (DC), and keratinocytes (KC). We hypothesize that specific alterations in chromatin structure and gene regulation in skin-homing T-cells and myeloid DC (mDC) underlie the effects of psoriasis-associated genetic variants. In pursuit of this hypothesis, we propose the following Specific Aims: 1. To increase the power and resolution of psoriasis GWAS. This will be accomplished by (a) meta-analysis of European-origin datasets; (b) completing a GWAS in 2,500 psoriasis cases and 2,500 controls of South Asian origin; and (c) trans-ethnic meta-analysis of European, South Asian, and Chinese samples. 2. To define eQTLs in psoriasis-relevant immunocytes. This will involve (a) mining existing gene variation and expression data from GTEx and ImmVar; (b) performing genotyping and imputation on 75 PsC cases and 75 controls with skin RNA-seq data; (c) performing RNA-seq on blood-derived resting vs. stimulated mDC and skin-homing CD4+ and CD8+ T-cells from these individuals; and (d) performing eQTL analysis. 3. To define chromatin-QTLs in psoriasis-relevant immunocytes. This will be accomplished by (a) mining relevant existing chromatin data from GTEx, ENCODE and the Roadmap Epigenomics Project; (b) using ATAC-seq to generate chromatin structural data and transcription factor (TF) binding footprints for resting vs. stimulated mDC and skin-homing CD4+ and CD8+ T-cells from the same 75 PsC cases and 75 controls from Aim 2; and (c) performing chromatin-QTL (chrQTL) analysis using data from Aims 2a and 3. 4. To relate psoriasis GWAS signals to psoriasis-relevant eQTLs and chrQTLs. This will be done by (a) integrating association signals from Aim 1, eQTLs from Aim 2, and chrQTLs and TF footprints from Aim 3; (b) further prioritizing these signals based on psoriasis immunobiology; and (c) testing the strongest candidate variants via genetic manipulation. These experiments will generate an unprecedented genetic/epigenetic resource that will help us understand the pathophysiology of psoriasis and other autoimmune diseases.